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Adverse drug reactions (ADRs) represent a significant threat to patients' safety in dentistry, necessitating proactive measures for prevention and treatment. However, identifying ADRs of dental and oral interest can be challenging, and underreporting remains a persistent issue globally. This paper illustrates a smart system to help Italian healthcare personnel, including dentists, in identifying and reporting dental and oral ADRs. This educational program is within a larger multi-regional project financed by the Italian Agency of Drugs (AIFA). The proposed system comprises a free online questionnaire on ADRs of dental interest (including specific items about awareness and attitudes), and after the free consultation of an atlas of clinical images of dental and oral ADRs linked with a digital synopsis of drugs potentially related to ADRs. This section of the project was presented in April 2023 at the 30th National Congress of the Italian College of University Professors of Dental Disciplines, and the system appears to hold tremendous potential to improve the knowledge of healthcare professionals on oral and dental ADRs. [ABSTRACT FROM AUTHOR]

Introduction: Adverse drug reactions (ADR) are directly related to public health and become the focus of public and media attention. At present, a large number of ADR events have been reported on the Internet, but the mining and utilization of such information resources is insufficient. Named entity recognition (NER) is the basic work of many natural language processing (NLP) tasks, which aims to identify entities with specific meanings from natural language texts. Methods: In order to identify entities from ADR event data resources more effectively, so as to provide valuable health knowledge for people, this paper introduces ALBERT in the input presentation layer on the basis of the classic BiLSTM-CRF model, and proposes a method of ADR named entity recognition based on the ALBERT-BiLSTM-CRF model. The textual information about ADR on the website "Chinese medical information query platform" (https://www.dayi.org. cn) was collected by the crawler and used as research data, and the BIO method was used to label three types of entities: drug name (DRN), drug component (COM), and adverse drug reactions (ADR) to build a corpus. Then, the words were mapped to the word vector by using the ALBERT module to obtain the character level semantic information, the context coding was performed by the BiLSTM module, and the label decoding was using the CRF module to predict the real label. Results: Based on the constructed corpus, experimental comparisons were made with two classical models, namely, BiLSTM-CRF and BERT-BiLSTM-CRF. The experimental results show that the F1 of our method is 91.19% on the whole, which is 1.5% and 1.37% higher than the other two models respectively, and the performance of recognition of three types of entities is significantly improved, which proves the superiority of this method. Discussion: The method proposed can be used effectively in NER from ADR information on the Internet, which provides a basis for the extraction of drugrelated entity relationships and the construction of knowledge graph, thus playing a role in practical health systems such as intelligent diagnosis, risk reasoning and automatic question answering. [ABSTRACT FROM AUTHOR]

Background: Medication adherence is a prerequisite to achieving beneficial treatment outcomes. In major depressive disorder, many patients fail to complete medication regimens, raising concern for poor treatment outcomes. It is usual to experience adverse drug reactions (ADRs) while taking antidepressants, and relative discomfort is reported by patients. Aims: The present review focuses on the presence of antidepressant-related side effects and the subsequent relationship with medication non-adherence. Methods: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. Following the preliminary research, the research question and eligibility criteria were created based on the PICO framework. All articles retrieved from the selected databases were exported to Covidence, a Systematic Review managing software tool. Two reviewers assessed the papers to identify the risk of bias using the Joanna Briggs Institute critical appraisal tool for cross-sectional studies. Seven studies with a low–moderate risk of bias fulfilled the eligibility criteria and were conducted from 2013 to 2020 in Europe, Africa and Asia. Results: The results demonstrated high levels of suboptimal adherence ranging from 46% to 83% amongst the studied population. A variety of side effects were reported by a significant number of participants predominantly with moderate severity. A correlation between the presence of ADRs and suboptimal rates of adherence to antidepressants was found. Somnolence and headaches among other unspecified ADRs were found to increase the dropout rates for selective serotonin reuptake inhibitors. Conclusions: The present study elucidates the need for effective interventions to facilitate antidepressant adherence and enhance doctor–patient communication, benefiting both the individuals and the healthcare system and leading to better clinical outcomes and reduction of relapse-related costs. [ABSTRACT FROM AUTHOR]

Introduction: Adverse drug reactions (ADRs) are harmful and unintended reactions to medicines given at standard doses through a proper route of administration for the purpose of prophylaxis, diagnosis, or treatment. Objective: The objective of this research paper was to assess median time to development of ADRs and associated factors among children HIV positive patients on antiretroviral treatment (ART) in North West Amhara Specialized Hospitals. Methods: The adverse drug effect survival time was estimated using the Kaplan–Meier survival method and log‐rank test curves was applied for analyze "time‐to‐event" data. Cox regression model was used to identify the associated factors. Adjusted hazard ratios with their respective 95% confidence intervals (CIs) were estimated and a value of p less than 0.05 was used to declare the presence of a significant association. Result: The overall incidence of ADRs was 0.67 (95% CI: 3.74–4.44) per 10,000 person‐year observation, with a median of 57 months. Adults are presenting with opportunistic Infections (OIs) experiences, baseline CD4 < 200 cells/µL counts, 1e, tenofovir disoproxil fumarate–lamivudine–efavirenz ART regimen, bedridden baseline functional status, World Health Organization (WHO) clinical stage II and III were notably associated with the incidence of ADRs development. Conclusion: ADRs were uncommon in this study. predictors, such as OIs experiences, a low CD4 count, ART regimen, an advanced WHO stage, and bedridden functional status were significantly associated with ADRs. [ABSTRACT FROM AUTHOR]

The detection of adverse drug reactions (ADRs) is an important piece of information for determining a patient’s view of a single drug. This study attempts to consider and discuss this feature of drug reviews in medical opinion-mining systems. This paper discusses the literature that summarizes the background of this work. To achieve this aim, the first discusses a survey on detecting ADRs and side effects, followed by an examination of biomedical text mining that focuses on identifying the specific relationships involving ADRs. Finally, we will provide a general overview of sentiment analysis, particularly from a medical perspective. This study presents a survey on ADRs extracted from drug review sentences on social media, utilizing and comparing different techniques. [ABSTRACT FROM AUTHOR]

Introduction: Drug treatment can be related to the development of adverse drug reactions (ADRs). Aim: In this paper, we evaluated ADRs in patients admitted to the Ambulatory of Pain Medicine of the University Hospital Renato Dulbecco in Catanzaro. Methods: We conducted a prospective analysis between 1 February 2021 and 20 July 2023 on patients with neuropathic pain referred to the Ambulatory of Pain Medicine of "Renato Dulbecco" University Hospital in Catanzaro (Calabria, Italy). Patients aged >18 years with clinical signs of neurologic pain and a score upon completing the Douleur Neuropathique en 4 Questions (DN4) questionnaire of ≥4 were included. The association between drugs and ADR or between drugs and drug–drug-interactions (DDIs) was evaluated using Naranjo's probability scale and Drug Interaction Probability Scale (DIPS), respectively. Results: During the study period, we analyzed 2370 patients referred to the ambulatory of pain medicine. After the evaluation of inclusion and exclusion criteria, 33.5% of patients were enrolled. All patients presented at least one comorbidity and daily used a mean of five drugs (range 3–11). Using the Naranjo score, the development of ADRs was documented in 112 patients (score 6). Using parametric and non-parametric statistical analysis, we failed to report an association between ADR and dosage or ADR and patient characteristics. Conclusion: Our results show the development of ADRs in 18% of patients with neuropathic pain. This low percentage of drug interaction could be a limitation in real life because it is probably due to the site of the study and the appropriate prescription of drugs. Therefore, it shows that it is necessary to motivate healthcare to pay attention to the prescription of drugs in poly-treated patients to reduce the risk of ADRs. [ABSTRACT FROM AUTHOR]

Copyright of Evaluation & Analysis of Drug-Use in Hospitals of China is the property of Evaluation & Analysis of Drug-Use in Hospitals of China Editorial Board and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Adverse Drug Reactions (ADRs) are an important public health issue as they can impose significant health and monetary burdens. This paper presents the engineering and use case of a Knowledge Graph, supporting the prevention of ADRs as part of a Clinical Decision Support System (CDSS) developed in the context of the PrescIT project. The presented PrescIT Knowledge Graph is built upon Semantic Web technologies namely the Resource Description Framework (RDF), and integrates widely relevant data sources and ontologies, i.e., DrugBank, SemMedDB, OpenPVSignal Knowledge Graph and DINTO, resulting in a lightweight and selfcontained data source for evidence-based ADRs identification. [ABSTRACT FROM AUTHOR]

Objectives: To investigate community pharmacists' attitudes, confidence, practice, knowledge, and barriers towards the management of oral side effects of asthma medications. Methods: A paper-based questionnaire was developed from previous research, trialled, and validated. Convenience sampling through web search was used to identify pharmacy practices across Cairns, Queensland, Australia. Practices were contacted by email and phone before hand-delivering and collecting questionnaires. Key findings: Thirty eight community pharmacist responses were descriptively analysed. Community pharmacists surveyed within the Cairns region feel that it is within their role to help manage the side effects of asthma medications. Many feel this is best conveyed during inhaler dispensing and instruction. Current advice is more prompted rather than preventative. Pharmacists routinely advise patients of mouth-rinsing following inhaler use, however the link to preventing side effects is not clearly communicated. Pharmacists are confident in recognizing and managing common side effects such as oral thrush and dry mouth, but fewer are aware of dental decay and gingivitis. Many identify a lack of guidelines as the largest barrier to providing preventive oral health advice. Conclusions: Cairns community pharmacists already self-perceive their role in the management of oral side effects of asthma medications. Advice given to patients is practical but does not clearly convey the causative associations between asthma medications and their potential oral side effects. Patient education is prompted more by enquiry rather than a preventative approach. The development of standardized practice protocols and integration within undergraduate degrees or continuing education may benefit the community–pharmacist delivered care. [ABSTRACT FROM AUTHOR]

Goserelin acetate is a gonadotropin‐releasing hormone analog that is commonly used in patients with prostate cancer, endometriosis, and precocious puberty. The side effects of the drug include allergic rash, flushing, excessive sweating, skin swelling at the injection site, sexual dysfunction, erectile dysfunction, and menopausal symptoms. However, erythema nodosum has so far not been reported. In this paper, we have presented the case of erythema nodosum caused by goserelin acetate and a review of the literature on its adverse effects, thus providing useful insights into clinical management and medication safety. [ABSTRACT FROM AUTHOR]

Background: Hospital readmissions due to medication-related problems occur frequently, burdening patients and caregivers emotionally and straining health care systems economically. In times of limited health care resources, interventions to mitigate the risk of medication-related readmissions should be prioritized to patients most likely to benefit. Focusing on general internal medicine patients, this scoping review aims to identify risk factors associated with drug-related 30-day hospital readmissions. Methods: We began by searching the Medline, Embase, and CINAHL databases from their inception dates to May 17, 2022 for studies reporting risk factors for 30-day drug-related readmissions. We included all peer-reviewed studies, while excluding literature reviews, conference abstracts, proceeding papers, editorials, and expert opinions. We also conducted backward citation searches of the included articles. Within the final sample, we analyzed the types and frequencies of risk factors mentioned. Results: After deduplication of the initial search results, 1159 titles and abstracts were screened for full-text adjudication. We read 101 full articles, of which we included 37. Thirteen more were collected via backward citation searches, resulting in a final sample of 50 articles. We identified five risk factor categories: (1) patient characteristics, (2) medication groups, (3) medication therapy problems, (4) adverse drug reactions, and (5) readmission diagnoses. The most commonly mentioned risk factors were polypharmacy, prescribing problems—especially underprescribing and suboptimal drug selection—and adherence issues. Medication groups associated with the highest risk of 30-day readmissions (mostly following adverse drug reactions) were antithrombotic agents, insulin, opioid analgesics, and diuretics. Preventable medication-related readmissions most often reflected prescribing problems and/or adherence issues. Conclusions: This study's findings will help care teams prioritize patients for interventions to reduce medication-related hospital readmissions, which should increase patient safety. Further research is needed to analyze surrogate social parameters for the most common drug-related factors and their predictive value regarding medication-related readmissions. [ABSTRACT FROM AUTHOR]

A potential complication of pharmacotherapy for a given patient is the possibility of various side effects of drugs, which are manifested in many ways and constitute iatrogenic causes of diseases. Among the systemic side effects of drugs, there are also those involving the urinary tract, although these are less reported in the literature. The use of numerous drugs—especially of anticholinergics or drugs with anticholinergic potential, opioid analgesics, non-steroidal anti-inflammatory drugs, antidepressants, first-generation antipsychotics (classic neuroleptics) and selected cardiovascular drugs (beta-blockers, thiazides potassium-sparing diuretics, statins), as well as others—may increase the risk of developing urological disorders, such as urinary retention or incontinence, urinary tract infections, urolithiasis, erectile dysfunction in men and retroperitoneal fibrosis. The purpose of this paper is to characterise the abovementioned drug-induced disorders of the lower urinary tract on the basis of a non-systematic literature review. [ABSTRACT FROM AUTHOR]

Older patients are prone to multimorbidity or related polypharmacy, which may cause various adverse drug reactions (ADRs) and a high incidence of drug‐related health problems. Although not often noted, ADRs include nutrition‐related adverse reactions. Aging, multiple illnesses, mental and psychological problems, declining physical function, and environmental factors can lead to decreased food intake and increased metabolic stress in older people, resulting in energy imbalances that cause malnutrition. ADRs can lead to appetite loss, followed by decreased food intake, which in turn causes malnutrition and deficiencies of various nutrients. However, these nutrition‐related ADRs have received less attention. This review article describes drug–nutrition interactions, with a particular focus on older patients. Geriatr Gerontol Int 2023; 23: 465–477. Pharmacotherapy is a very important means of disease prevention and treatment for older patients. However, adverse drug reactions can have a significant negative impact on the health of older people. In this paper, the impact of drug therapy on nutritional status, dietary intake, the absorption and excretion of nutrients, and metabolism, with a focus on older people, is reviewed. [ABSTRACT FROM AUTHOR]

Adverse drug reactions (ADRs) are a prominent cause of morbidity and mortality and higher healthcare expenditures. Healthcare professionals (HCPs) play a crucial role in ADR reporting through spontaneous reporting systems, but under-reporting is their major limitation. The goal of this study is to evaluate HCPs' knowledge, attitude, and practice regarding ADR reporting as well as the factors that influence reporting using research papers that are currently available. A literature search was conducted using sources such as PubMed, Scopus, and Google Scholar to find studies that evaluated HCPs' knowledge, attitudes, and practices regarding ADRs reporting in Ethiopia. A standard procedure of systematic review protocol was used to conduct this review. Demographic factors, sample size, response rate, survey delivery, HCP working setting, and encouraging and discouraging factors of ADR reporting were extracted from articles. A total of 17 articles were included in the systematic review out of 384. The number of HCPs in the included studies ranged from 62 to 708. Response rate ranges from 76.1% to 100%. Most of the research included in this evaluation looked at HCPs, who worked in hospitals. When pharmacists were compared to other HCPs, they were more likely to report ADRs; because they had higher knowledge, attitude, and practice. Lack of understanding, unavailability of reporting forms, uncertainty about the causal relationship between the drug and ADR, and failure to report because the ADR was well known were among the common hurdles to ADR reporting identified in research. To improve reporting, educational initiatives and continued training in pharmacovigilance and ADRs are frequently recommended considerations. In Ethiopia, there is a pressing need to close the gap in HCP knowledge, attitudes, and practice regarding PV and ADR reporting. To address this point, specific educational interventions based on existing gaps in ADR reporting should be developed and integrated into the health education curriculum or provided as in-service training after graduation. [ABSTRACT FROM AUTHOR]

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Adverse Drug Reactions (ADRs) are a crucial public health issue due to the significant health and monetary burden that they can impose. Real-World Data (RWD), e.g., Electronic Health Records, claims data, etc., can support the identification of potentially unknown ADRs and thus, they could provide raw data to mine ADR prevention rules. The PrescIT project aims to create a Clinical Decision Support System (CDSS) for ADR prevention during ePrescription and uses OMOP-CDM as the main data model to mine ADR prevention rules, based on the software stack provided by the OHDSI initiative. This paper presents the deployment of OMOP-CDM infrastructure using the MIMIC-III as a testbed. [ABSTRACT FROM AUTHOR]

Adverse drug reactions (ADRs), which are harmful physical reactions of patients to drug treatments, are inherent to the nature of drugs; the reactions can occur with any drug and are becoming a leading cause of patient morbidity and mortality during medical procedures. ADRs can be hazardous and even fatal to patients. In traditional methods, ADRs are detected through clinical trials. To obtain a comprehensive collection of ADRs, sufficient experimental samples and time are required before a drug comes to the market, which is not a realistic possibility. Moreover, even if extensive clinical trials are performed, many undetected ADRs might still be discovered after a drug is released to the market. ADRs can lead to disastrous consequences for humanity, which obviates a dramatically increased need for precise predictions of potential ADRs as early as possible. In this paper, we propose an encoder-decoder framework based on attention mechanism and the long short-term memory (LSTM) model to predict potential ADRs. We regard the prediction of ADRs as a sequence-to-sequence problem and improve the encoder-decoder framework based on the attention mechanism to learn the interrelationships between ADRs. Unlike other classical methods utilizing molecular drug structures, our model is based solely on ADRs, which is an independent but parallel approach compared to traditional methods. We capitalize on the mask method to generate the target data and use the 5-fold cross-validation method to cyclically verify the performance of our proposed model. Based on the Top-k accuracy test results, our model outperforms the baseline models in potential ADRs predictions. [ABSTRACT FROM AUTHOR]

Recent years have witnessed booming data on drugs and their associated adverse drug reactions (ADRs). It was reported that these ADRs have resulted in a high hospitalisation rate worldwide. Therefore, a tremendous amount of research has been carried out to predict ADRs in the early phases of drug development, with the goal of reducing possible future risks. The pre-clinical and clinical phases of drug research can be time-consuming and cost-ineffective, so academics are looking forward to more extensive data mining and machine learning methods to be applied in this field of study. In this paper, we try to construct a drug-to-drug network based on non-clinical data sources. The network presents underlying relationships between drug pairs according to their common ADRs. Then, multiple node-level and graph-level network features are extracted from this network, e.g., weighted degree centrality, weighted PageRanks, etc. After concatenating the network features to the original drug features, they were fed into seven machine learning models, e.g., logistic regression, random forest, support vector machine, etc., and were compared to the baseline, where there were no network-based features considered. These experiments indicate that all the tested machine-learning methods would benefit from adding these network features. Among all these models, logistic regression (LR) had the highest mean AUROC score (82.1%) across all ADRs tested. Weighted degree centrality and weighted PageRanks were identified to be the most critical network features in the LR classifier. These pieces of evidence strongly indicate that the network approach can be vital in future ADR prediction, and this network-based approach could also be applied to other health informatics datasets. [ABSTRACT FROM AUTHOR]

Introduction: Pharmacovigilance plays an important role in patient safety and rationalizing the use of medicines. It helps in identifying the frequency of adverse drug reactions (ADRs), their causes, and the associated risk factors. Pharmacovigilance activities are facilitated through adverse drug reactions monitoring centers (AMCs) in most of the institutions. Aim: The objective of this paper is to provide an overview to the health care professionals regarding ADRs reported from the associated hospitals of Maulana Azad Medical College (MAMC) and the pharmacovigilance activities undertaken. Observations: Maulana Azad Medical College, Department of Pharmacology was recognized as an AMC in 2014 under the Pharmacovigilance Program of India (PvPI). The AMC established a way for reporting ADRs both by spontaneously and through active monitoring of ADRs from different wards. The causality assessment of all ADR reports collected is done. The program was informed by a college pharmacovigilance committee, emails, and by putting posters in the hospital nursing stations. Fourteen training workshops for doctors and pharmacists and two training workshops exclusively for nurses have been conducted so far on pharmacovigilance. In 2017, a program to sensitize doctors working in the Delhi government hospital was started. A total of 854 healthcare workers have been sensitized. The center has reported a total of 2572 ADRs to the National Coordination Centre (NCC) at Indian Pharmacopoeia Commission until December 2021. ADRs reported were highest in the age group of 20 to 59 years. Most of the reports were from the department of T.B. and Chest (n=589, 23.8%). The most common class of medicines implicated in causing ADRs was antimicrobials (n=1100, 44%). Among the ADRs reported, the majority were mild (n=1451, 81.1%) with 346 (18.8%) reported as serious. Conclusion: A system for reporting ADRs on campus has been established. The pattern of ADRs reported to this ADR monitoring center is comparable to the national and global data. Hospital-based ADR monitoring and reporting programs are very crucial to identify and quantify the risks associated with the use of medicines. The pharmacovigilance program at MAMC is a commitment and a small step towards patient safety. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Beijing University of Traditional Chinese Medicine is the property of Journal of Beijing University of Traditional Chinese Medicine and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: The pharmacoepidemiology of the long-term benefits and harms of medicines in pregnancy and breastfeeding has received little attention. The impact of maternal medicines on children is increasingly recognised as a source of avoidable harm. The focus of attention has expanded from congenital anomalies to include less visible, but equally important, outcomes, including cognition, neurodevelopmental disorders, educational performance, and childhood ill-health. Breastfeeding, whether as a source of medicine exposure, a mitigator of adverse effects or as an outcome, has been all but ignored in pharmacoepidemiology and pharmacovigilance: a significant 'blind spot'. Whole-population data on breastfeeding: why we need them Optimal child development and maternal health necessitate breastfeeding, yet little information exists to guide families regarding the safety of medicine use during lactation. Breastfeeding initiation or success may be altered by medicine use, and breastfeeding may obscure the true relationship between medicine exposure during pregnancy and developmental outcomes. Absent or poorly standardised recording of breastfeeding in most population databases hampers analysis and understanding of the complex relationships between medicine, pregnancy, breastfeeding and infant and maternal health. The purpose of this paper is to present the arguments for breastfeeding to be included alongside medicine use and neurodevelopmental outcomes in whole-population database investigations of the harms and benefits of medicines during pregnancy, the puerperium and postnatal period. We review: 1) the current situation, 2) how these complexities might be accommodated in pharmacoepidemiological models, using antidepressants and antiepileptics as examples; 3) the challenges in obtaining comprehensive data. Conclusions: The scarcity of whole-population data and the complexities of the inter-relationships between breastfeeding, medicines, co-exposures and infant outcomes are significant barriers to full characterisation of the benefits and harms of medicines during pregnancy and breastfeeding. This makes it difficult to answer the questions: 'is it safe to breastfeed whilst taking this medicine', and 'will this medicine interfere with breastfeeding and/ or infants' development'? [ABSTRACT FROM AUTHOR]

Adverse drug reactions (ADRs) is a challenge in modern healthcare, particularly given the increasing complexity of drug therapy, an ageing population, rising multimorbidity, and a high patient turnover. The core activity of detecting potential ADRs over the last half century has been spontaneous reporting systems. A recent Norwegian regulation commits healthcare professionals other than physicians and dentists to report serious ADRs. In this discussion paper, we share our preliminary experience with a training programme using nurses as ADR advocates to stimulate ADR reporting among the clinical staff in a hospital department. Central Illustration: Central Illustration Nurses as adverse drug reaction (ADR) reporting advocates participating in pharmacovigilance (PV) at the Department of Heart Disease, Haukeland University Hospital, Bergen, Norway. The department is a 'lighthouse' (inspiring other departments) in PV in the hospital, and cooperates with the drug committee and the regional PV centre. Commitment is achieved through the department manager and the medical director in the hospital. In addition, a new national regulation commits healthcare professionals other than physicians and dentists to report serious ADRs. [ABSTRACT FROM AUTHOR]

India confines more than 17% of the world's population and has a diverse genetic makeup with several clinically relevant rare mutations belonging to many sub-group which are undervalued in global sequencing datasets like the 1000 Genome data (1KG) containing limited samples for Indian ethnicity. Such databases are critical for the pharmaceutical and drug development industry where diversity plays a crucial role in identifying genetic disposition towards adverse drug reactions. A qualitative and comparative sequence and structural study utilizing variant information present in the recently published, largest curated Indian genome database (IndiGen) and the 1000 Genome data was performed for variants belonging to the kinase coding genes, the second most targeted group of drug targets. The sequence-level analysis identified similarities and differences among different populations based on the nsSNVs and amino acid exchange frequencies whereas a comparative structural analysis of IndiGen variants was performed with pathogenic variants reported in UniProtKB Humsavar data. The influence of these variations on structural features of the protein, such as structural stability, solvent accessibility, hydrophobicity, and the hydrogen-bond network was investigated. In-silico screening of the known drugs to these Indian variation-containing proteins reveals critical differences imparted in the strength of binding due to the variations present in the Indian population. In conclusion, this study constitutes a comprehensive investigation into the understanding of common variations present in the second largest population in the world and investigating its implications in the sequence, structural and pharmacogenomic landscape. The preliminary investigation reported in this paper, supporting the screening and detection of ADRs specific to the Indian population could aid in the development of techniques for pre-clinical and post-market screening of drug-related adverse events in the Indian population. [ABSTRACT FROM AUTHOR]

Context: Real-life data consist of exhaustive data which are not subject to selection bias. These data enable to study drug-safety profiles but are underused because of their temporality, necessitating complex models (i.e., safety depends on the dose, timing, and duration of treatment). We aimed to create a data-driven pipeline strategy that manages the complex temporality of real-life data to highlight the safety profile of a given drug.Methods: We proposed to apply the weighted cumulative exposure (WCE) statistical model to all health events occurring after a drug introduction (in this paper HCQ) and performed bootstrap to select relevant diagnoses, drugs and interventions which could reflect an adverse drug reactions (ADRs). We applied this data-driven pipeline on a French national medico-administrative database to extract the safety profile of hydroxychloroquine (HCQ) from a cohort of 2,010 patients.Results: The proposed method selected eight drugs (metopimazine, anethole trithione, tropicamide, alendronic acid & colecalciferol, hydrocortisone, chlormadinone, valsartan and tixocortol), twelve procedures (six ophthalmic procedures, two dental procedures, two skin lesions procedures and osteodensitometry procedure) and two medical diagnoses (systemic lupus erythematous, unspecified and discoid lupus erythematous) to be significantly associated with HCQ exposure.Conclusion: We provide a method extracting the broad spectrum of diagnoses, drugs and interventions associated to any given drug, potentially highlighting ADRs. Applied to hydroxychloroquine, this method extracted among others already known ADRs. [ABSTRACT FROM AUTHOR]

Adverse drug reaction is a major public health issue. The increasing availability of medico-administrative databases offers major opportunities to detect real-life pharmacovigilance signals. We have recently adapted a pharmacoepidemiological method to the large dimension, the WCE (Weigthed Cumulative Exposure) statistical model, which makes it possible to model the temporal relationship between the prescription of a drug and the appearance of a side effect without any a priori hypothesis. Unfortunately, this method faces a computational time problem. The objective of this paper is to describe the implementation of the WCE statistical model using Graphics Processing Unit (GPU) programming as a tool to obtain the spectrum of adverse drug reactions from medico-administrative databases. The process is divided into three steps: pre-processing of care pathways using the Python library Panda, calculation of temporal co-variables using the Python library "KeOps", estimation of the model parameters using the Python library "PyTorch" - standard in deep learning. Programming the WCE method by distributing the heaviest portions (notably spline calculation) on the GPU makes it possible to accelerate the time required for this method by 1000 times using a computer graphics card and up to 10,000 times with a GPU server. This implementation makes it possible to use WCE on all the drugs on the market to study their spectrum of adverse effects, to highlight new vigilance signals and thus to have a global vigilance tool on medico-administrative database. This is a proof of concept for the use of this technology in epidemiology. [ABSTRACT FROM AUTHOR]

The prevalence of adverse drug reactions (ADRs) associated with medications has emerged as a pressing global concern, impacting patients worldwide. Addressing the mitigation and prevention of ADRs to enhance patient safety stands as a paramount challenge within the healthcare community. This paper introduces a novel approach featuring the complex q-rung picture fuzzy Aczel–Alsina prioritized ordered weighted arithmetic (Cq-RPFAAPOWA) aggregation operator (AO) and the complex q-rung picture fuzzy Aczel–Alsina prioritized ordered weighted geometric (Cq-RPFAAPOWG) AO, each incorporating priority weightings. Furthermore, the paper devises a robust multi-attribute decision-making (MADM) methodology that employs these operators to discern suitable medication alternatives for patients with minimal or no impact from ADRs. In contrast to conventional operators, the Cq-RPFAAPOWA and Cq-RPFAAPOWG AOs effectively curtail potential redundancy in relationship assessments throughout the decision-making process. To exemplify the viability of the proposed MADM method, a comprehensive quantitative model is presented, showcasing its practical applicability. An exhaustive case study in ADR assessment empirically underscores the superiority of this approach over existing strategies. Importantly, the study underscores that drug selection based on the severity of ADRs stands as the most influential factor in elevating the public healthcare system. These findings offer valuable insights into decision-making processes and present actionable recommendations for policymakers, empowering them to make well-informed and impactful enhancements in the selection of pharmacological therapies. [ABSTRACT FROM AUTHOR]

Drug-related adverse events or adverse drug reactions (ADRs) are currently partially or substantially under-reported. ADR reporting systems need to expand their focus to include sex- and gender-related factors in order to understand, prevent, or reduce the occurrence of ADRs in all people, particularly women. This scoping review describes adverse drug reactions reported to international pharmacovigilance databases. It identifies the drug classes most commonly associated with ADRs and synthesizes the evidence on ADRs utilizing a sex- and gender-based analysis plus (SGBA+) to assess the differential outcomes reported in the individual studies. We developed a systematic search strategy and applied it to six electronic databases, ultimately including 35 papers. Overall, the evidence shows that women are involved in more ADR reports than men across different countries, although in some cases, men experience more serious ADRs. Most studies were conducted in higher-income countries; the terms adverse drug reactions and adverse drug events are used interchangeably, and there is a lack of standardization between systems. Additional research is needed to identify the relationships between sex- and gender-related factors in the occurrence and reporting of ADRs to adequately detect and prevent ADRs, as well as to tailor and prepare effective reporting for the lifecycle management of drugs. [ABSTRACT FROM AUTHOR]

Background: Adverse drug reactions with an outcome of death represent the most serious consequences and are inherently important for pharmacovigilance. The nature and characteristics of drug-related deaths are to a large extent unknown in the Chinese population. This study aims to characterize drug-related deaths by analysis of individual case safety reports (ICSRs) with an outcome of death in China. Methods: The characteristics of death ICSRs were analyzed by descriptive statistics of a large multi-provincial pharmacovigilance database in China. Results: There were 1,731 ICSRs with an outcome of death, representing 0.95% of all serious cases and 0.05% of all reported ICSRs. Most death ICSRs (78.57%) were reported by medical institutions. Only 16.00% of death ICSRs were reported by manufacturers or distributors. The reporting rate of death ICSRs in the age group of 0–4 years was significantly higher than patients aged 5–64 years. Patients aged over 64 years had the highest reporting rate of death ICSRs. Male patients generally had a higher reporting rate of death ICSRs than female patients. However, the reporting rate of female patients exceeded that of male patients in the age group of 20–34 years. Among 3,861 drugs implicated, ceftriaxone sodium with 146 (3.78%) records of death ranked first. Dexamethasone with 131 (3.39%) records of death ranked second. Qingkailing, an injectable traditional Chinese medicine with 75 (1.94%) records of death, ranked the fifth most frequently implicated medicine. Conclusion: Young children and elderly patients have a higher risk of drug-related deaths than patients aged 5–64 years. Female patients generally have a lower risk of drug-related deaths than male patients. However, female patients of reproductive age (aged 20–34 years) have a higher risk of drug-related deaths than male patients, hinting that physiological changes and drug uses for child bearing, giving birth, or birth control may significantly increase the risk of death for female patients aged 20–34 years. This paper suggests more research on the safe use of drugs for young children, elderly patients, and female patients of reproductive ages. Pharmacovigilance databases can be valuable resources for comprehensive understanding of drug-related problems. [ABSTRACT FROM AUTHOR]

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Objective: Drug interactions are a common cause of morbidity and mortality and may require prompt discontinuation of therapeutic regimens due to harmful side effects. Patients with acute coronary syndromes are likely to be prescribed multiple medications that are metabolized through the cytochrome P450 system, increasing the probability for drug interaction. Atorvastatin and simvastatin are both well known to interact with the oral P2Y12 agent ticagrelor. The purpose of this paper is to describe the interaction of ticagrelor with rosuvastatin leading to rhabdomyolysis, which is less clearly defined in the literature. Method: We report a case of a 74-year-old male who presented with bilateral lower extremity weakness and difficulty ambulating for one month after being prescribed ticagrelor for a drug eluting stent, in the setting of already being on rosuvastatin. His clinical picture and laboratory findings were consistent with a diagnosis of rhabdomyolysis. His medications were adjusted to a regimen of clopidogrel and alirocumab. One month later, he returned to his baseline status. Results: The mechanism of interaction between rosuvastatin and ticagrelor appears to be multifactorial. It may be caused by CYP450-mediated metabolism from a small amount of crossover between isoenzymes. Ticagrelor may also cause acute kidney injury, increasing the concentration of rosuvastatin. Other mechanisms of interaction include genetic differences in the organic anion transporter polypeptides and transportation through p-glycoprotein. Conclusion: Future pharmacokinetic studies are warranted to better understand the interaction. [ABSTRACT FROM AUTHOR]

The world bank has classified 80 economies based on their Gross National Income (GNI) per capita as High-Income. European Medicines Agency (EMA), Food and Drug Administration (FDA), and Pharmaceuticals and Medical Devices Agency (PMDA) are the major regulatory stakeholders driving global pharmacovigilance regulations. The purpose of this article is to describe pharmacovigilance systems and processes in high-income countries, particularly those that are also members of the International Conference on Harmonization (ICH). All high-income countries are members of the WHO PIDM. The income level of a country has a direct relationship with medicine safety measures. All ten pioneering members of the Uppsala monitoring centre are from high-income countries and were the first responders after the thalidomide tragedy by making drug evaluation committees, introducing the ADR reporting forms and taking safety measures. Despite access to the VigiBase, some countries have separate databases for managing and analyzing data like Canada Vigilance online database, FDA Adverse Event Reporting System, the French pharmacovigilance database and European Union's system Eudravigilance. All high-income countries have robust pharmacovigilance systems. USFDA and EMA are the world leaders in the field of pharmacovigilance. Most high-income countries follow EMA guidelines. Medicine safety is directly influenced by a country's income level. [ABSTRACT FROM AUTHOR]

Erythema multiforme major, an immune-mediated skin reaction to infections or medications with oral involvement, should be taken into account as a potential side effect of several vaccines, including SARS-CoV- 2. Correct patient history collection allows prompt recognition and subsequent successful medical management with oral corticosteroids. [ABSTRACT FROM AUTHOR]

Purpose: We report a case of a patient experiencing paroxysmal supraventricular tachycardia after infusing doxophylline. Methods: Clinical evaluations and the electrocardiogram were performed by specialists. Findings: Our patient felt palpitations and chest distress after intravenous Doxophylline. The electrocardiogram showed paroxysmal supraventricular tachycardia. There was no evidence to prove that there was any problem with his heart, liver, and kidney. According to the Naranjo Adverse Drug Reaction probability scale, paroxysmal supraventricular tachycardia has a probable relationship with Doxophylline. Implications: The paroxysmal supraventricular tachycardia is a rare but reasonable adverse reaction of Doxophylline, which should be paid more attention. [ABSTRACT FROM AUTHOR]

The relationship between chronic kidney disease (CKD) and cognitive function has received increased attention in recent years. Antibacterial agents (ABs) represent a critical component of therapy regimens in patients with CKD due to increased susceptibility to infections. Following our reviewing work on the neurocognitive impact of long-term medications in patients with CKD, we propose to focus on AB-induced direct and indirect consequences on cognitive function. Patients with CKD are predisposed to adverse drug reactions (ADRs) due to altered drug pharmacokinetics, glomerular filtration decline, and the potential disruption of the blood–brain barrier. ABs have been identified as a major cause of ADRs in vulnerable patient populations. This review examines the direct neurotoxic effects of AB classes (e.g. beta-lactams, fluoroquinolones, aminoglycosides, and metronidazole) on the central nervous system (CNS) in patients with CKD. We will mainly focus on the acute effects on the CNS associated with AB since they are the most extensively studied effects in CKD patients. Moreover, the review describes the modulation of the gut microbiota by ABs, potentially influencing CNS symptoms. The intricate brain–gut–kidney axis emerges as a pivotal focus, revealing the interplay between microbiota alterations induced by ABs and CNS manifestations in patients with CKD. The prevalence of antibiotic-associated encephalopathy in patients with CKD undergoing intravenous AB therapy supports the use of therapeutic drug monitoring for ABs to reduce the number and seriousness of ADRs in this patient population. In conclusion, elucidating AB-induced cognitive effects in patients with CKD demands a comprehensive understanding and tailored therapeutic strategies that account for altered pharmacokinetics and the brain–gut–kidney axis. [ABSTRACT FROM AUTHOR]

Opioids are the strongest analgesics available and are crucial in the treatment of acute and chronic pain. The line between these critical medications and how they are used beyond standard therapeutics in cases such as abuse, misuse, and medication errors needs to be understood, as it affects their safety, efficacy, and manner of use. The aim of this systematic review was to identify what is known about the adverse events resulting from the abuse, misuse, and medication errors associated with opioid use. A systematic search was conducted in the PubMed®, Scopus® and, EBSCO® databases to retrieve studies from the inception to December 2023 reporting abuse, misuse, and medication errors associated with medicinal opioid use. Two authors independently screened titles and abstracts and full text according to eligibility using Covidence® software. Full articles were examined by two independent reviewers, and disagreements were resolved by a third reviewer. The risk of bias was assessed by the JBI's critical appraisal tools. A total of 934 articles were screened by their title and abstract. Then, 151 articles were selected for full text screening. Of these, 34 studies were eligible for inclusion in this review. The included studies varied significantly in their population sizes, ranging from 9 individuals to 298,433 patients, and encompassed a diverse demographic, including all ages and both sexes. The studies consistently reported a range of adverse events associated with opioid use. Fentanyl, morphine, oxycodone, tramadol, and hydrocodone were frequently implicated. The data heterogeneity in this field resulted in challenges in drawing conclusions. The review highlights that some opioids, particularly fentanyl, morphine, and oxycodone, are frequently associated with preventable adverse drug reactions, abuse, and medication errors, underscoring the need for robust preventative measures and ongoing research to mitigate opioid-related harm. [ABSTRACT FROM AUTHOR]